使用深度学习和混合视觉/力控制的机器人拾取和装配

K. Almaghout, R. A. Boby, Mostafa Othman, A. Shaarawy, A. Klimchik
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引用次数: 3

摘要

本文讨论了使用深度学习和使用视觉和力反馈组合的装配来拾取无特征的圆柱体。目标检测采用YOLO技术,用于检测机器人拾取的目标。即使在杂乱的环境中,也可以识别出物体。讨论了圆柱物体在紧间隙孔中的装配问题。该方法包括混合控制,即沿装配平面的位置控制和沿装配平面法线方向的力控制。在KUKA iiwa机器人上实现了该方法,并给出了结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robotic Pick and Assembly Using Deep Learning and Hybrid Vision/Force Control
Pick up of featureless cylinders using deep learning and assembly using combination of visual and force feedback is discussed in this article. Object detection using YOLO technique is used to detect the object for robotic pick up. It was possible to identify the object even in cluttered environments. The assembly of the cylindrical object in a hole with tight clearance is also discussed. The method involves hybrid control i.e., position control along the assembly plane and force control along the direction of normal to the plane. The method is implemented using KUKA iiwa robot and the results are presented.
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